#!/usr/bin/env python
# coding: utf-8

# # Introduction: The basics of Notebook
# 
# \begin{equation}
# \int_0^\infty f(x) dx
# \end{equation}
# 
# You can write standard Python:

# In[1]:


from math import *
print(cos(pi))
print(pi)
2*pi


# In[2]:


import math
from scipy import *
from numpy import *
print(dir(math))
print( log2(10) )
print( math.log(10,2), math.log2(10) )
#info(log2)


# ## Two modes
# 
# **Command Mode** and **Edit Mode**
# 
# "Return" and "Esc" to switch between **Command** and **Edit** modes
# 
# **To Execute** : "Shift Return"
# 
# **To return to Edit mode** : "Return/double click"
# 
# **hide long cell output** double click

# In[3]:


import requests
resp = requests.get("http://www.physics.rutgers.edu/grad/509/")
resp.content


# ## Two (main) cell types
# 
# In a different type of cell, you can:
# 
# * write Markdown
# * embed LaTex equation in it
# 
# So you can add comments to your code explaining that, to calculate your cycling speed, you must make use of the fact that
# 
# $[x,p_x]=i \hbar$.

# ## Some basic operations and keystrokes:
# 
# Toggling toolbars.
# 
# * Return and Esc
# * A (new cell before) and B (new cell after)
# * X (cut cell), C (copy cell), V (paste cell)
# * DD (delete cell)
# 
# The different types of Return:
# * Shift-Return
# * Ctrl-Return
# * Alt-Return
# 
# Choosing cell type:
# * M (for Markdown)
# * Y (for code)

# Use ! to use shell comman right inside notebook

# In[7]:


get_ipython().system('ls -ltr')
get_ipython().system('pwd')


# ## Sharing your notebooks
# 
# You can just send people the .ipynb files; they'll contain your input and (optionally) your output.
# 
# Other ways to view and run:
# 
# * **nbconvert** - e.g. convert to static HTML, LaTeX, PDF, Python script, etc
# * **Github & Bitbucket** - rendered, but static, e.g. for [qhue](https://github.com/quentinsf/qhue)
# * **nbviewer** - http://nbviewer.jupyter.org
# * **binder** or **Azure notebooks** - take a github repo with notebooks, and run them in a Docker session   \[mybinder.org\]
# * **jupyterhub** - run locally to make jupyter environments available to users
# 
# ---

# ## Understanding the kernel setting
# 
# The running Python environment is determined by the *kernel setting* of your notebook and not, for example, by the virtualenv you happen to be in.
# 
# Here's where your shell environment will find python, pip etc:

# In[8]:


get_ipython().system('which python')


# That's often the Python that's running the notebook server.

# And here's the Python running *this notebook*, defined by the choice of kernel:

# In[9]:


import sys
sys.executable


# ## And lastly...
# 
# Close and Halt
#